Self-organizing single-hop wireless sensor network using a genetic algorithm: Longer lifetimes and maximal throughputs

In wireless sensor networks (WNSs), the network structure, which specifies how sensor nodes work, is greatly affects the network lifetime. To build the optimum network structure in cluster-based WSN may differs from round to round depending on a set of sensor nodes factors, i.e, remaining energy, vulnerability index, and the distance from BS. Getting the intended optimum structure is non trivial process, which includes determining the appropriate number of clusters, electing a cluster head (CH) for each cluster, and assigning each sensor node to a clusters. Recently, several studies propose CH selection protocols with predefined number of clusters. The present work introduces a new Genetic Algorithm (GA) based protocol that aims to get the optimum network structure for single-hop cluster model in WSN. This structure may differ after each round. The results show that the proposed GA-based method leads to more network lifetime and throughput. Also, it is more efficient in the context of a dynamic environment.